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so much to learn and such little time

As a 31yo Principal Engineer with 20 years of programming experience and 15 years in the industry, I I would add that you should know Vacuum fluctuations Planck-scale quantum foam Feynman path integrals Quantum electrodynamics Quantum chromodynamics The Standard-Model Lagrangian

HI GUYS! MY NAME IS OMAH LAY AND I AM THE GREATEST OF MY GENERATION, I DON’T HAVE PROOFS RIGHT NOW BUT THERE WILL BE A LOT IN THE FUTURE. THANKS YOURS TRULY BOY ALONE

In 5 years, when Ozempic is widespread, there's going to be a huge influx of beautiful people into the dating pool who will also have the patience, perspective and sympathy they developed from their time overweight. It'll be an amazing time to be single.

Small Language Models (SLMs) are the future of Agentic AI, claim @NVIDIA researchers. Moreover, they offer a method for converting existing agent systems from using LLMs to SLMs that could work in practice. Here are the details:

do not build Infinite Jest (V), do not build the infinite AI TikTok slop machine, do not build the P-zombie AI boy/girlfriend, do not build the child-eating short-form video blackhole, do not build the human-feedback-optimized diffusion transformer porn generator. save yourselves

After uni is when you see life properly. No school exams to distract you from the fact that you are fucked.

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As long as the companies selling you agentic AI have a human CEO, human developers, and human salespeople, they clearly don't have any agents to sell.

some intern at mckinsey is probably slopcoating a report on this but let me give you an insider news: most large corps are not happy with the agentic systems & POCs they’ve done this year. 2025 was supposed to be the year of agents. so far it’s been the year of letdowns.

a sperm bank implies the existence of sperm markets which further implies the existence of high frequency sperm trading

Indian Police providing psychiatric treatment after rescuing 🥴😂

Just so you know, since the release of the "Attention is All You Need" paper in June 2017 and the open-weight BERT model that followed after it, all pretrained transformers had a context size of 512 tokens, and training longer context models "didn't make sense because of the

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recently seeing the rise of "plastic software" while this software is fast to create and consume, it's next-to-impossible to refactor and reuse

I woke up Single No one is pregnant Handsome The weather is cold No one is pregnant Life is great